Futures: WR Cordarrelle Patterson, Playmaker

Cordarrelle Patterson may not be a playmaker according to Football Outsider’s Playmaker Score, but the elusive receiver with skills as a receiver that many top prospects-turned-busts lacked is worth the risk in my book. Find out where I think the Combine, production, and film study have a place in this discussion of this versatile, athletic, wildcard.

When it comes to evaluating football talent, I believe analytics can be a part of the conversation. The Playmaker Score is a good example.

I think the Playmaker Score is a nice attempt at data mining where Vince Verhei has reverse-engineered a formula with the hope of developing a successful model to predict future results. The score does enough to have value in discussions about specific wide receiver prospects, but Playmaker is not the entire conversation.

I believe player evaluation can be likened to a three-legged, wooden table:

Technical skill

College production

Athleticism

If one of these legs is missing or not factored into an evaluation enough, the table doesn’t function as it should. The fourth factor is character, but I think it’s best considered as liquid -– either it enhances, like a wood stain, or degrades, like water spot.

Scouting is such a hit-or-miss process because no one has figured out a way to consistently make all three legs of the table functional for every player evaluation. Nor can they predict if the player’s character will enhance or ruin the “table.”

When we first devised our Playmaker Score projection system to predict NFL success for wide receivers, we looked at individual collegiate production only. A second version added team statistics to account for players who might have seen their numbers inflated by prolific passing offenses. This year, with Playmaker Score 3.0, we’ve added Combine data for the first time. Now we’re measuring not just football skills, but raw physical talent.

We’ve made one other fundamental change to Playmaker Score, and it involves the way collegiate data is handled. In the past, using career totals considerably underrated those players who were so spectacular that they skipped their senior seasons and entered the draft early, while using per-game numbers depressed the ratings for guys who had lots of one- and zero-catch games as freshmen and sophomores before exploding as juniors and seniors. We tried to get around this by using a mix of career totals and per-game data, but the results were a little confusing and somewhat illogical. So we’ve gone back to the drawing board, and we’re now using the numbers from each player’s best season. This makes the most sense because it rewards the biggest stars at the expense of more mediocre players who pad their statistics with multiple starting seasons. Obviously, there’s now a danger of overestimating one-year wonders, but we’re working on some methods to correct for that in the future.

We checked the numbers for every receiver drafted from 2005 to 2009, a group of 149 players. That gave us five years’ worth of recent history, while giving every player at least three years to break out in the NFL. For each player, we determined their NFL success by dividing their career receiving yardage by the number of seasons that had passed since, whether they were still in the league or not. We also compared their Combine numbers to their NFL statistics and checked which were most accurate when it came to predicting NFL success.

Playmaker Score addresses the basic question of how good the quarterback is when it comes to giving his receiver opportunities for production. However, I think zeroing in on passes per game as a factor makes Playmaker Score a slave to a specific kind of receiver production that doesn’t tell the entire story.

Problems Endemic to Football Evaluation

Playmaker does not fully address all the dimensions of production that can make a wide receiver a playmaker. Yards after catch is a significant example, although not a purposeful oversight. The staff here at Football Outsiders would love to have this data, but the college game does not supply it in an easily available format.

However, this is part of the reason why I think the revised 2011 Playmaker Scores missed on A.J. Green (227 points) and Randall Cobb (136 points), but it liked Jonathan Baldwin (464 points) and Torrey Smith (448 points). I think Baldwin and Smith played in offenses that were suited to what Playmaker Score rewards players for: red-zone production and longer plays from pitch-to-catch. It doesn’t factor in ball carrying of any sort, and that’s part of what it missed about Green and Cobb.

I liked Smith’s prospects, but I wasn’t high on Baldwin. One of the reasons reflects what is missing from Playmaker: it is a formula based on production and athleticism (as measured by certain sprints and jumps, at least) but it doesn’t account for technical skill.

However, I’m jumping the gun on technique. The athleticism factor also requires more discussion.

The way Playmaker uses Combine data is a problem endemic to the area of football evaluation. I believe the primary function of the Combine should first be to determine which players have the baseline speed, strength, quickness, and size to perform at an NFL level. Instead, there is too much emphasis placed on stronger-faster-higher-longer.

Playmaker’s inclusion of Combine measurements assumes that the better (certain) Combine numbers, the better the player. I think most people make this assumption, and it’s easy to do: Some people believe Calvin Johnson is a better player than Dez Bryant because he jumps higher, runs faster, and does it in a bigger body.

Athleticism is a baseline requirement, but there is a point where a player’s value can be inaccurately inflated or depressed because technical skill or capacity to learn the game isn’t properly accounted for. To give examples, we have A.J. Green on one hand, and Robert Meachem on the other.

Green had actually scored high in the previous version of Playmaker (v2.0) but does not fare well in the current version because of the Combine metrics. His NFL Combine metrics were NFL-quality, but not stellar. Yet what the formula misses, game observation catches: aplayer who gets the most from his athleticism because he integrates his physical and technical skill sets at a high level to make plays.

Meachem, on the other hand, was a fast prospect, but he couldn’t catch the ball with his hands away from his body. I admired his efforts as a senior at Tennessee to extend his arms to the football, but he often had to revert to a trap technique.

One example I recall was a game in Tennessee against LSU. Meachem dropped three passes in the first quarter alone while trying to use proper hands technique. He then reverted to a trap technique for the rest of the game.

While I admired Meachem for trying, some technical skills are more difficult to learn at this stage of football than others. Receivers who don’t make receptions with their hands away from their frames are unlikely to acquire these skills when they transition to the pro game.

This issue is what I would term a fatal error. Difficulty securing the ball after contact from a defender during the act of the reception can also be a fatal error when it comes to evaluating the technical skill potential of a prospect.

Although Meachem eventually made some strides to improve this skill, he has never been comfortable enough to make a complete transition. He has not become the impact player commensurate with his first-round grade. These two flaws were why I didn’t like Meachem’s chances of doing that, and he proved me right.

As for other examples from 2011, I loved Green (my No. 1 rated receiver in 2011), Randall Cobb (No. 3) and Torrey Smith (No. 5). In contrast, Jonathan Baldwin (No.13) was an overrated commodity in my book. Green, Cobb and Smith demonstrated excellent skill versus contact and both Green and Cobb were strong players after the catch. Baldwin’s hands techniques were spotty and his technique and conceptual execution of routes were inconsistentat best.

I think a better way to view measures of athleticism is to, as I said, first assess if it meets the baseline requirements to play in the NFL. Then assess if that player also meets baselines for skill level/capacity to learn the skills.

Once an evaluator establishes that the prospect has the basic tools, I think the fast-stronger-longer-higher quality of the Combine measurements become a refining characteristic to the evaluation process. The same goes for productivity metrics.

The problem is that we want to throw these tools into the evaluation process at a premature stage. As a result, the data can often overestimate (or underestimate) the value of players.